Triple
T18485630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EdReports.org |
E451680
|
entity |
| Predicate | subjectAreaReviewed |
P18525
|
FINISHED |
| Object | mathematics instructional materials |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: mathematics instructional materials | Statement: [EdReports.org, subjectAreaReviewed, mathematics instructional materials]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectAreaReviewed Context triple: [EdReports.org, subjectAreaReviewed, mathematics instructional materials]
-
A.
subjectAreaLevel
Indicates the hierarchical level or depth of specialization of a particular subject area in relation to others.
-
B.
primarySubjectArea
Indicates the main academic or topical field to which something (such as a work, course, or resource) is most centrally related.
-
C.
hasResearchArea
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
D.
subjectMatterScope
chosen
Indicates the thematic or topical domain that an action, statement, or resource pertains to or falls within.
-
E.
assessmentAreaDefinedBy
Indicates that the scope or domain of an assessment is specified or delimited by a particular area or boundary.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e531d722808190a97828cae8e3846e |
completed | April 19, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69e469d671088190b619de96ea6f92ab |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:35 a.m.